Distributed aero-engine control systems architecture selection using multi-objective optimisation

被引:13
|
作者
Thompson, HA
Chipperfield, AJ
Fleming, PJ
Legge, C
机构
[1] Univ Sheffield, Rolls Royce Technol Ctr Control & Syst Engn, Dept Automat Control & Syst Engn, Sheffield S1 3JD, S Yorkshire, England
[2] Rolls Royce PLC, Bristol BS12 7QE, Avon, England
关键词
multidisciplinary optimisation; multiobjective optimisation; distributed systems;
D O I
10.1016/S0967-0661(99)00011-8
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The cost of em bedding intelligence into sensors and actuators directly has dramatically reduced over the past 10 years. This has led to the recent explosion of smart sensors and actuators available from manufacturers. Initially, these have been developed for the process control industries but increasingly applications in aerospace are being found. Integration of intelligent components is being carried out in an ad hoc manner by incorporating smart elements in inherently centralised architectures. This paper discusses the application of a multidisciplinary, multiobjective optimisation approach to a military gas turbine engine control system architecture design, where implementation benefits and penalties must be systematically evaluated. (C) 1999 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:655 / 664
页数:10
相关论文
共 50 条
  • [41] Multi-objective optimisation using fuzzy logic
    Yu, DW
    Lai, E
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MECHANICAL TRANSMISSIONS, 2001, : 322 - 327
  • [42] Multi-task Optimisation for Multi-objective Feature Selection in Classification
    Lin, Jiabin
    Chen, Qi
    Xue, Bing
    Zhang, Mengjie
    PROCEEDINGS OF THE 2022 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2022, 2022, : 264 - 267
  • [43] A multi-objective optimisation-based software environment for control systems design
    Joos, HD
    2002 IEEE INTERNATIONAL SYMPOSIUM ON COMPUTER AIDED CONTROL SYSTEM DESIGN PROCEEDINGS, 2002, : 7 - 14
  • [44] High-dimensional multi-objective optimization algorithm for combustion chamber of aero-engine based on artificial neural network-multi-objective particle swarm optimization
    Liang, Shuang
    Li, Lang
    Tian, Ye
    Song, Wenyan
    Le, Jialing
    Guo, Mingming
    Xiong, Shihang
    Zhang, Chenlin
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING, 2023, 237 (11) : 2577 - 2593
  • [45] Using multi-objective metaheuristics for the optimal selection of positioning systems
    Ficco, Massimo
    Pietrantuono, Roberto
    Russo, Stefano
    SOFT COMPUTING, 2016, 20 (07) : 2641 - 2664
  • [46] Using multi-objective metaheuristics for the optimal selection of positioning systems
    Massimo Ficco
    Roberto Pietrantuono
    Stefano Russo
    Soft Computing, 2016, 20 : 2641 - 2664
  • [47] Technology of solving multi-objective problems of control of systems with distributed parameters
    Rapoport E.Y.
    Pleshivtseva Y.E.
    Rapoport, E. Ya. (edgar.rapoport@mail.ru), 1600, Allerton Press Incorporation (53): : 316 - 328
  • [48] Transmission delay/packet dropout robustness analysis of distributed control system of aero-engine
    Li R.
    Guo Y.
    Jiang C.
    Chen Y.
    Hangkong Dongli Xuebao/Journal of Aerospace Power, 2017, 32 (06): : 1441 - 1446
  • [49] Multi-Objective Particle Swarm Optimisation (PSO) for Feature Selection
    Xue, Bing
    Zhang, Mengjie
    Browne, Will N.
    PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, 2012, : 81 - 88
  • [50] A Multi-objective and Multidisciplinary Optimisation Algorithm for Microelectromechanical Systems
    Farnsworth, Michael
    Tiwari, Ashutosh
    Zhu, Meiling
    Benkhelifa, Elhadj
    NEO 2016: RESULTS OF THE NUMERICAL AND EVOLUTIONARY OPTIMIZATION WORKSHOP NEO 2016 AND THE NEO CITIES 2016 WORKSHOP, 2018, 731 : 205 - 238